Skip to main content

HDDM is a python module that implements Hierarchical Bayesian estimation of Drift Diffusion Models.

Project description

This little convenience package extracts the cython based Navarro and Fuss likelihoods from the HDDM package for fitting hierarchical versions of the Drift Diffusion Model .

The code of this repo is essentially taken from the HDDM package.

The Copyright information for the original package is:

Author:

Thomas V. Wiecki, Imri Sofer, Mads L. Pedersen, Alexander Fengler, Lakshmi Govindarajan, Krishn Bera, Michael J. Frank

Contact:

thomas.wiecki@gmail.com, imri_sofer@brown.edu, madslupe@gmail.com, alexander_fengler@brown.edu, krishn_bera@brown.edu, michael_frank@brown.edu

Web site:

https://hddm.readthedocs.io

Github:

http://github.com/hddm-devs/hddm

Mailing list:

https://groups.google.com/group/hddm-users/

Copyright:

This document has been placed in the public domain.

License:

HDDM is released under the BSD 2 license.

Version:

0.9.7

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hddm_wfpt-0.1.0.tar.gz (219.6 kB view details)

Uploaded Source

Built Distributions

hddm_wfpt-0.1.0-cp311-cp311-win_amd64.whl (141.8 kB view details)

Uploaded CPython 3.11 Windows x86-64

hddm_wfpt-0.1.0-cp311-cp311-musllinux_1_1_x86_64.whl (806.1 kB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

hddm_wfpt-0.1.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (796.3 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

hddm_wfpt-0.1.0-cp311-cp311-macosx_11_0_arm64.whl (136.8 kB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl (148.3 kB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_universal2.whl (272.2 kB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64)

hddm_wfpt-0.1.0-cp310-cp310-win_amd64.whl (141.1 kB view details)

Uploaded CPython 3.10 Windows x86-64

hddm_wfpt-0.1.0-cp310-cp310-musllinux_1_1_x86_64.whl (740.7 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

hddm_wfpt-0.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (723.8 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

hddm_wfpt-0.1.0-cp310-cp310-macosx_11_0_arm64.whl (135.5 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl (146.3 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_universal2.whl (268.8 kB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64)

hddm_wfpt-0.1.0-cp39-cp39-win_amd64.whl (141.0 kB view details)

Uploaded CPython 3.9 Windows x86-64

hddm_wfpt-0.1.0-cp39-cp39-musllinux_1_1_x86_64.whl (740.1 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

hddm_wfpt-0.1.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (723.5 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

hddm_wfpt-0.1.0-cp39-cp39-macosx_11_0_arm64.whl (136.4 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl (148.0 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_universal2.whl (271.5 kB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

File details

Details for the file hddm_wfpt-0.1.0.tar.gz.

File metadata

  • Download URL: hddm_wfpt-0.1.0.tar.gz
  • Upload date:
  • Size: 219.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for hddm_wfpt-0.1.0.tar.gz
Algorithm Hash digest
SHA256 eab87edfa49f36df4e1a590f7392c734239faaeac482b6baa12f4a5ac938aa53
MD5 3a4575474b8d234966edd216035d3917
BLAKE2b-256 1db062e48d0ead53f30b99a0300da9a7020cf87906e7c0ff245af74f3d6b62bb

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 7205a20be2f1c93a7a4c883ccf6806b6a8c2d53aa689994b7222ac19f4eb9fc4
MD5 86a3c69a97f54ade3bcf48e362a24697
BLAKE2b-256 2d5404db72a0bb4c97d8eb4e5063e78abccebeba9ae3a8bf68572cf84c4701f0

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 c86c7457736aa06368be7e6135f2292bfbb02033506d2545e520334319719f76
MD5 86895293bb2a42eb44b664f48b75296e
BLAKE2b-256 b959830f9e9a9ebb1a1d0ae039244cb86c2f5e27a3ae8d27216a3ff1824b42a6

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1fa74dbb87cd41f7e49d822cde43fc72d65a5735ffe8be167f8563784f08ce41
MD5 0ab85f0f311f9d27eafaf5a97a2db613
BLAKE2b-256 e244423dcf9d119a1379875d28a7ac82df91b7da9e9096be986a79f901713635

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f4d0668bb1ac5c7358fd965fd6ef8145fdbae0beca07420908ad39c26a205aad
MD5 7c690cd3a0f45fa32a47660f89db99f7
BLAKE2b-256 22211aed7cad53751aeda819cada31aff450224cfc9d87609c2697fb24b4a555

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 f3124e663e00d5542dfe9eecb966908d78a1749c67df7e0bbac2eb946d483105
MD5 58aacf6e155f4304b71f3be500acaf5d
BLAKE2b-256 d28ba90216f640a51cae084e7d51d049f7fe24936aa4e91925a6e764186c644e

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 0e0f3de1d0c1e743bfba894ac3388f1ce8fa6bca537e85c18b55a40eba620ece
MD5 d4712093fc924df3a428b5f371945e07
BLAKE2b-256 309090a6a2e78311d71c670827f8d3dd331b94ceb84a9070d9fe6248bf353d80

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 09edee7d6923619f29c63055b0549e2b2f0a3c1971c797ce0d9f813216655934
MD5 52ad07e627b78e02539ba385ac282416
BLAKE2b-256 b7c45ca8419adffc9e245d1f7cc55ec58778824a7c2a263b50ade6467c4c0175

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5ce97f546b8f7cad84833b0b5553812938ec968492b7b18a29a71809ee5f6a87
MD5 b06de443a47359b727a13b5fd3c1964a
BLAKE2b-256 f30fd0f1194dbfafb0e3fbb52ffe097b40fb42251a5b48f649ebece6fa6cd822

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 30e0a8f43dcbff961dbaca7434bf8323b64a148d4739b6ddb1d92997d51931c2
MD5 49d8b183b3f4fd35022b139a20637345
BLAKE2b-256 7c3722db940b4e17c09fc53b1afdc450c84fa2badd5f6b23dfb8428c5d88a43b

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 198eca31249c75a23e474a0ad79bbed103a6e8807716dcbc5f5b68228d5a5dea
MD5 a9bf78f4093f7a3fb71c73f043eb5d81
BLAKE2b-256 89cab72fdf48e42f91a115a4e3a0d41af5804570178b1dd2e0bb525999de64da

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9b19681393d483b2d2fcb7d3b975abab052db6e0f481468b24b97db708351bdf
MD5 b3507f4312cdaf629c72ed6b36612eb8
BLAKE2b-256 e0edb1e4ab0b11962e3d893fb964f2a1c7c4344b37db99a706559b5ac43fac48

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 5cf511c0f4408b74e3fa18dd488844f9b9e007de9a737d6274b720741c5e367a
MD5 cfc072fdda096e7d43af4f2d4aa1107b
BLAKE2b-256 28cc22bd1cb8f1be363b02f380f4dfbfcc73a82c4a0a27c7d55cec6cd33f1f2a

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: hddm_wfpt-0.1.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 141.0 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.5

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2508b62ea95e166517cb590d5281b3184f7b2e3b1aacddc37281636a95a626b0
MD5 ececede1f09a34e5676e615a37f617fb
BLAKE2b-256 3fa352a4d1dda1f895775725c57d7ef4fac4550d83b1a646b7870ead1dcb53ad

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 72400d0c297767a61be12f4febe5eae02f688c01f97b0d0544b6ac861cbd720b
MD5 464d6573b9ffba57f2761091ec885b40
BLAKE2b-256 9daecb9051157bf50255ac32e8f6731e887dab8eca1a138ccf97b50b816a52e8

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0ac43e893fe05125080aef841ee6f2257870f17c25c9a63d3fa65e8f83d7ca6e
MD5 b0a3ff3750eaeca75aa5032a10ab446e
BLAKE2b-256 a982b2d42e3158261f05834e5cffd7d718802e2056b1c15d16cfee75da8d68a6

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 76abef43d3b60a410209fd6f07b3d02814e3f67bc2f7d064790444d2f3cbabb1
MD5 8e3f5765c542d9f83a236bf12f1d4800
BLAKE2b-256 6847a5cfa37543b8d568a388044ffa92f378056544d81787da5210f20b214f21

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 28b3848de67ef49f78e9aff92b278f5b202fcbef855a7c272995f8be3dcd525c
MD5 df577bd0fc28173d3dfef7fefcb0342e
BLAKE2b-256 9d022dc659eb42758a7317c0c9aea283bc62b478c9df1a8f2211d43cbd8c9f8d

See more details on using hashes here.

File details

Details for the file hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for hddm_wfpt-0.1.0-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 52c53c4a4ce8922e5eb08004273d3afa35dd13933c2df7df65c9c2581ad16020
MD5 d5b429691aae03ccd39be238248b3d60
BLAKE2b-256 28f9deb9a080dae416f3631b096f95997533edf57ab36f9a041fa27b35a91fa5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page